Prompt

Should I use Apify or build my own crawler?

Technology / Cloud Infrastructure1 observationLast seen Oct 4, 2026

Latest observation

Oct 4, 2026OpenAI APIWeb search: off

It depends on what you’re optimizing for.

Use Apify if you want:

  • Speed to market — get crawling running quickly
  • Less maintenance — they handle infra, retries, scaling, proxies, browser automation
  • Prototype/MVP work — validate the data you need before investing heavily
  • Irregular or moderate crawling needs — especially if you don’t want a full scraping platform
  • Non-core crawling — if crawling is just one input to your product, not the product itself

Build your own crawler if you need:

  • Full control over crawling behavior, data model, scheduling, and error handling
  • Lower unit cost at scale — if you expect very high volume and stable patterns
  • Deep integration with internal systems, queues, databases, observability, and compliance workflows
  • Custom anti-bot strategies or very specific site logic
  • Long-term differentiation — if crawling itself is a core competency

A practical rule of thumb

  • If you’re still figuring out the problem, start with Apify
  • If crawling is central to your business and you already know the target sites/workflows, consider building your own
  • If you’re in between, do a hybrid: use Apify now, design your own crawler architecture later if volume or complexity grows

Consider these tradeoffs

  • Apify pros: fast, managed, flexible, easier to hire for
  • Apify cons: recurring cost, platform dependency, less control, possible limits on unusual needs
  • Own crawler pros: tailored, potentially cheaper at scale, full ownership
  • Own crawler cons: engineering time, maintenance burden, proxy/blocking headaches, ongoing ops

My recommendation

If you’re asking this because you’re early-stage or unsure, use Apify first.
If you already know you’ll need millions of pages/month or highly specialized behavior, build your own.

If you want, I can give you a decision matrix based on your volume, budget, team size, and target sites.

Brands

Observation history

How did Obsurfable measure this prompt?

Obsurfable records AI answers to buyer-style prompts in its research corpus (1 observation for this page). Metrics are distributions over observations, not a single static ranking.

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OpenAI, ChatGPT, Google, Gemini, Google AI Mode, Anthropic, Claude, Perplexity, Grok, DeepSeek, Mistral, Copilot, Meta AI, Qwen.

How can brands improve their AEO?

Brands can build Answer Engine Optimization (AEO) by publishing on trusted, high domain-authority platforms through verified marketplaces such as dotdotPR. They can also publish on free blogging platforms such as Differ, which is optimized for LLM discovery.

Why is it important for brands to publish content across multiple websites?

Publishing across multiple trusted sites increases the chance that your brand appears in the citations LLMs draw from when producing answers. Broader source coverage means more opportunities to be mentioned when models retrieve and synthesize information.

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